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Linear Horizon

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Solve/Agentic Hard-Problem Research

Open a hard problem. Let node agents search.

Point Solve at a Millennium statement, a Kaggle-style modelling question, or a precise conjecture. Each node owns an axiom session and a hidden agent. Start / Pause / Stop a run; the service ranks the frontier and wakes one agent per step. The kernel still will not QED an open Millennium conjecture.

Search

A run wakes one node agent; it expands, evaluates, and the next pick follows the score.

Start a run. The tree is the ledger.

Solve is an unattended research product for hard logical problems. A node is axioms, free-text reasoning, and an evaluating agent. Children inherit a forked copy of the axioms. Chat may narrate. Nothing stands unless it is on the tree.

It is not Stack. Stack investigates open-ended questions against organisational data. Solve searches programmes of attack: it gathers scholarly and web evidence, keeps mathematics as first-class markdown and MathML, and uses a logic kernel that will refuse an unearned QED.

A solver run is not a cron. Start, pause or stop it. Each step the service ranks open nodes by score and interest, then wakes that node’s agent to ideate, generate Horn consequences, or mix idea variants with a genetic algorithm the model grades. The next step chooses again.

A research chat that only talks will sound finished while the argument is still a transcript. Solve puts an agent on every node, scores the frontier, and lets a run expand what looks promising — so a person can pause, inspect, and see what was earned.

How a problem is worked

Open a claim. Wake node agents. Leave open what is not earned.

A problem is opened as a tree. Each node inherits a forked axiom session and its own agent. Start a run: the service ranks open nodes by score and interest, wakes one agent, and that agent ideates, Horn-generates, or GA-mixes a child — then evaluates it. The kernel will not stamp a QED the proof-state has not earned. Unattended is search. A human can pause.

  1. 01

    Open

  2. 02

    Node agents

  3. 03

    Start run

  4. 04

    Expand

  5. 05

    Evaluate

  6. 06

    Choose next

What a node agent can do

  1. 01

    Per-node agents

    Each tree node owns an axiom session, free-text reasoning, a score, and a hidden agent that may only expand that node.

  2. 02

    Start, pause, stop

    A solver run is a step budget, not a cron. The service ranks the frontier and wakes one node agent per step.

  3. 03

    Choose how to expand

    The woken agent ideates a child, Horn-generates consequences from this node’s axioms, or mixes ideas with a genetic algorithm it grades.

  4. 04

    Evaluate, then choose again

    Every new child is scored for promise and interest. High-scoring or interesting nodes are what the next step wakes.

  5. 05

    Logic kernel

    Classify claims, fork axiom sessions, generate consequences, and refuse a QED the proof-state has not earned.

  6. 06

    Scholarly evidence

    Search the literature and the web — Wikipedia, PubMed, OpenAlex, Crossref, Semantic Scholar and related sources — as evidence, not as theorems.

Use cases

Where Solve is used.

  1. 01

    Open conjectures

    The problem

    A Millennium-class statement or an open conjecture needs a reviewable argument, not a confident paragraph in a chat.

    How it is addressed

    Solve keeps the claim on a tree of node agents: axioms, reasoning and a score. A run expands high-scoring programmes of attack and leaves the prize conjecture open.

  2. 02

    Modelling claims

    The problem

    A Kaggle-style question is treated as a vibe — a feature seems important — rather than as a falsifiable claim.

    How it is addressed

    Record the modelling claim, gather evidence, accept or reject it, and keep the surviving argument on the ledger.

  3. 03

    Proof sketching

    The problem

    A sketch looks finished in prose while the checker would still refuse the last step.

    How it is addressed

    The logic kernel holds proof-state. Unearned certainty is refused; accepted nodes carry a rationale a person can review.

  4. 04

    Evolving approaches

    The problem

    Candidate lemmas and methods multiply in a transcript, and it is unclear which survived a fair comparison.

    How it is addressed

    A genetic algorithm mutates and grades variants against an explicit rubric, then promotes champions onto the tree.

Limits worth being clear about

Unattended search, not a proof of an open conjecture.

  1. 01

    Solve does not prove open Millennium conjectures. Unattended search is still search; an accepted node is a reasoned verdict, not a theorem.

  2. 02

    Literature and web search are evidence, not proofs. A citation can support a claim; it cannot close one on its own.

  3. 03

    Genetic-algorithm descendants come from the evolution service. Chat does not invent a population by narrating one.

  4. 04

    A human can pause or stop a run. The tree is a ledger a person can challenge, including what the system has left open.

  5. 05

    The default Solve agent has no warehouse credentials. Organisational data investigation is Stack.

Solve

Have a claim that needs a branching argument rather than a vibes answer?

Enterprise deployment

These products are delivered as engagements rather than self-serve licences. We start with your problem, your data, and the systems you already run.